902 resultados para Density-based Scanning Algorithm


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High-density oligonucleotide (oligo) arrays are a powerful tool for transcript profiling. Arrays based on GeneChip® technology are amongst the most widely used, although GeneChip® arrays are currently available for only a small number of plant and animal species. Thus, we have developed a method to improve the sensitivity of high-density oligonucleotide arrays when applied to heterologous species and tested the method by analysing the transcriptome of Brassica oleracea L., a species for which no GeneChip® array is available, using a GeneChip® array designed for Arabidopsis thaliana (L.) Heynh. Genomic DNA from B. oleracea was labelled and hybridised to the ATH1-121501 GeneChip® array. Arabidopsis thaliana probe-pairs that hybridised to the B. oleracea genomic DNA on the basis of the perfect-match (PM) probe signal were then selected for subsequent B. oleracea transcriptome analysis using a .cel file parser script to generate probe mask files. The transcriptional response of B. oleracea to a mineral nutrient (phosphorus; P) stress was quantified using probe mask files generated for a wide range of gDNA hybridisation intensity thresholds. An example probe mask file generated with a gDNA hybridisation intensity threshold of 400 removed > 68 % of the available PM probes from the analysis but retained >96 % of available A. thaliana probe-sets. Ninety-nine of these genes were then identified as significantly regulated under P stress in B. oleracea, including the homologues of P stress responsive genes in A. thaliana. Increasing the gDNA hybridisation intensity thresholds up to 500 for probe-selection increased the sensitivity of the GeneChip® array to detect regulation of gene expression in B. oleracea under P stress by up to 13-fold. Our open-source software to create probe mask files is freely available http://affymetrix.arabidopsis.info/xspecies/ webcite and may be used to facilitate transcriptomic analyses of a wide range of plant and animal species in the absence of custom arrays.

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A new sparse kernel density estimator is introduced. Our main contribution is to develop a recursive algorithm for the selection of significant kernels one at time using the minimum integrated square error (MISE) criterion for both kernel selection. The proposed approach is simple to implement and the associated computational cost is very low. Numerical examples are employed to demonstrate that the proposed approach is effective in constructing sparse kernel density estimators with competitive accuracy to existing kernel density estimators.

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We present five new cloud detection algorithms over land based on dynamic threshold or Bayesian techniques, applicable to the Advanced Along Track Scanning Radiometer (AATSR) instrument and compare these with the standard threshold based SADIST cloud detection scheme. We use a manually classified dataset as a reference to assess algorithm performance and quantify the impact of each cloud detection scheme on land surface temperature (LST) retrieval. The use of probabilistic Bayesian cloud detection methods improves algorithm true skill scores by 8-9 % over SADIST (maximum score of 77.93 % compared to 69.27 %). We present an assessment of the impact of imperfect cloud masking, in relation to the reference cloud mask, on the retrieved AATSR LST imposing a 2 K tolerance over a 3x3 pixel domain. We find an increase of 5-7 % in the observations falling within this tolerance when using Bayesian methods (maximum of 92.02 % compared to 85.69 %). We also demonstrate that the use of dynamic thresholds in the tests employed by SADIST can significantly improve performance, applicable to cloud-test data to provided by the Sea and Land Surface Temperature Radiometer (SLSTR) due to be launched on the Sentinel 3 mission (estimated 2014).

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This contribution proposes a novel probability density function (PDF) estimation based over-sampling (PDFOS) approach for two-class imbalanced classification problems. The classical Parzen-window kernel function is adopted to estimate the PDF of the positive class. Then according to the estimated PDF, synthetic instances are generated as the additional training data. The essential concept is to re-balance the class distribution of the original imbalanced data set under the principle that synthetic data sample follows the same statistical properties. Based on the over-sampled training data, the radial basis function (RBF) classifier is constructed by applying the orthogonal forward selection procedure, in which the classifier’s structure and the parameters of RBF kernels are determined using a particle swarm optimisation algorithm based on the criterion of minimising the leave-one-out misclassification rate. The effectiveness of the proposed PDFOS approach is demonstrated by the empirical study on several imbalanced data sets.

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A new sparse kernel density estimator is introduced based on the minimum integrated square error criterion for the finite mixture model. Since the constraint on the mixing coefficients of the finite mixture model is on the multinomial manifold, we use the well-known Riemannian trust-region (RTR) algorithm for solving this problem. The first- and second-order Riemannian geometry of the multinomial manifold are derived and utilized in the RTR algorithm. Numerical examples are employed to demonstrate that the proposed approach is effective in constructing sparse kernel density estimators with an accuracy competitive with those of existing kernel density estimators.

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We establish a methodology for calculating uncertainties in sea surface temperature estimates from coefficient based satellite retrievals. The uncertainty estimates are derived independently of in-situ data. This enables validation of both the retrieved SSTs and their uncertainty estimate using in-situ data records. The total uncertainty budget is comprised of a number of components, arising from uncorrelated (eg. noise), locally systematic (eg. atmospheric), large scale systematic and sampling effects (for gridded products). The importance of distinguishing these components arises in propagating uncertainty across spatio-temporal scales. We apply the method to SST data retrieved from the Advanced Along Track Scanning Radiometer (AATSR) and validate the results for two different SST retrieval algorithms, both at a per pixel level and for gridded data. We find good agreement between our estimated uncertainties and validation data. This approach to calculating uncertainties in SST retrievals has a wider application to data from other instruments and retrieval of other geophysical variables.

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A new sparse kernel density estimator with tunable kernels is introduced within a forward constrained regression framework whereby the nonnegative and summing-to-unity constraints of the mixing weights can easily be satisfied. Based on the minimum integrated square error criterion, a recursive algorithm is developed to select significant kernels one at time, and the kernel width of the selected kernel is then tuned using the gradient descent algorithm. Numerical examples are employed to demonstrate that the proposed approach is effective in constructing very sparse kernel density estimators with competitive accuracy to existing kernel density estimators.

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A new sparse kernel density estimator is introduced based on the minimum integrated square error criterion combining local component analysis for the finite mixture model. We start with a Parzen window estimator which has the Gaussian kernels with a common covariance matrix, the local component analysis is initially applied to find the covariance matrix using expectation maximization algorithm. Since the constraint on the mixing coefficients of a finite mixture model is on the multinomial manifold, we then use the well-known Riemannian trust-region algorithm to find the set of sparse mixing coefficients. The first and second order Riemannian geometry of the multinomial manifold are utilized in the Riemannian trust-region algorithm. Numerical examples are employed to demonstrate that the proposed approach is effective in constructing sparse kernel density estimators with competitive accuracy to existing kernel density estimators.

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This paper presents a study on wavelets and their characteristics for the specific purpose of serving as a feature extraction tool for speaker verification (SV), considering a Radial Basis Function (RBF) classifier, which is a particular type of Artificial Neural Network (ANN). Examining characteristics such as support-size, frequency and phase responses, amongst others, we show how Discrete Wavelet Transforms (DWTs), particularly the ones which derive from Finite Impulse Response (FIR) filters, can be used to extract important features from a speech signal which are useful for SV. Lastly, an SV algorithm based on the concepts presented is described.

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The complex of Brookhart Ni(α-diimine)Cl2 (1) (α-diimine = 1,4-bis(2,6- diisopropylphenyl)-acenaphthenediimine) has been characterized after impregnation on silica (S1) and MAO-modified silicas (4.0, 8.0 and 23.0 wts.% Al/SiO2 called S2, S3 and S4, respectively). The treatment of these heterogeneous systems with MAO produces some active catalysts for the polymerization of the ethylene. A high catalytic activity has been gotten while using the system supported 1/S3 (196 kg of PE/mol[Ni].h.atm; toluene, Al/Ni = 1000, 30ºC, 60 min and atmospheric pressure of ethylene). The effects of polymerization conditions have been tested with the catalyst supported in S2 and the best catalytic activity has been gotten with solvent hexane, MAO as cocatalyst, molar ratio Al/Ni of 1000 and to the temperature of 30°C (285 kg of PE/mol[Ni].h.atm). When the reaction has been driven according to the in situ methodology, the activity practically doubled and polymers showed some similar properties. Polymers products by the supported catalysts showed the absence of melting fusion, results similar to those gotten with the homogeneous systems by DSC analysis. But then, polymers gotten with the transplanted system present according to the GPC’s curves the polydispersity (MwD) varies between 1.7 and 7.0. A polyethylene blend (BPE/LPE) was prepared using the complex Ni(α-diimine)Cl2 (1) (α-diimine = 1,4-bis(2,6-diisopropylphenyl)-acenaphthenediimine) and {TpMs*}TiCl3 (2) (TpMs* = hydridobis(3-mesitylpyrazol-1-yl)(5-mesitylpyrazol-1-yl)) supported in situ on MAO-modified silica (4.0 wts. -% Al/SiO2, S2). Reactions of polymerization of ethylene have been executed in the toluene in two different temperatures (0 and 30°C), varying the molars fraction of nickel (xNi), and using MAO as external cocatalyst. To all temperatures, the activities show a linear variation tendency with xNi and indicate the absence of the effect synergic between the species of nickel and the titanium. The maximum of activity have been found at 0°C. The melting temperature for the blends of polyethylene produced at 0 °C decrease whereas xNi increases indicating a good compatibility between phases of the polyethylene gotten with the two catalysts. The melting temperature for the blends of polyethylene showed be depend on the order according to which catalysts have been supported on the MAO-modified silica. The initial immobilization of 1 on the support (2/1/S2) product of polymers with a melting temperature (Tm) lower to the one of the polymer gotten when the titanium has been supported inicially (1/2/S2). The observation of polyethylenes gotten with the two systems (2/1/S2 and 1/2/S2) by scanning electron microscopy (SEM) showed the spherical polymer formation showing that the spherical morphology of the support to been reproduced. Are described the synthesis, the characterization and the catalytic properties for the oligomerization of the ethylene of four organometallics compounds of CrIII with ligands ([bis[2-(3,5-dimethyl-1-pyrazolyl)ethyl]amine] chromium (III) chloride (3a), [bis[2-(3,5- dimethyl-l-pyrazolyl)ethyl]benzylamine] chromium (III) chloride (3b), [bis[2-(3,5-dimethyl-lpyrazolyl) ethyl]ether] chromiun(III)chloride (3c), [bis[2-(3-phenyl-lpyrazolyl) ethyl]ether]chromiun(III)chloride (3d)). In relation of the oligomerization, at exception made of the compounds 3a, all complex of the chromium showed be active after activation with MAO and the TOF gotten have one effect differentiated to those formed with CrCl3(thf)3. The coordination of a tridentate ligand on the metallic center doesn't provoke any considerable changes on the formation of the C4 and C6, but the amount of C8 are decrease and the C10 and C12+ have increased. The Polymers produced by the catalyst 3a to 3 and 20 bar of ethylene have, according to analyses by DSC, the temperatures of fusion of 133,8 and 136ºC respectively. It indicates that in the two cases the production of high density polyethylene. The molar mass, gotten by GPC, is 46647 g/mols with MwD = 2,4 (3 bar). The system 3c/MAO showed values of TOF, activity and selectivity to different α-olefins according to the pressure of ethylene uses. Himself that shown a big sensibility to the concentration of ethylene solubilized.

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In the present work, the anodic oxide films of Al, Al-Cu 4.5% and Al-Si 6.5% alloys are formed using direct and pulse current. In the case of Al-Cu and Al-Si alloys, the electrolyte used contains sulfuric acid and oxalic acid, meanwhile for Al the electrolyte contains sulfuric acid only. Al-Cu alloy was submitted to a heat treatment in order to decrease the effect of inter metallic phase theta upon the anodic film structure. Fractured samples were observed using a field emission gun scanning electron microscope JSM-6330F at (LME)/Brazilian Synchrotron Light Laboratory (LNLS), Campinas, SP, Brazil. The oxide film images enable evaluation of the pore size and form with a resolution similar to the transmission electron microscope (TEM) resolution. It is also observed that the anodizing process using pulse current produces an irregular structure of pore walls, and by direct cur-rent it is produced a rectilinear pore wall. (c) 2005 Elsevier B.V. All rights reserved.

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Low frequency admittance measurements are used to determine the density of interface states in metal-insulator-semiconductor diodes based on the unintentionally doped, p-type semiconductor poly(3-hexylthiophene). After vacuum annealing at 90 degrees C, interface hole trapping states are shown to be distributed in energy with their density decreasing approximately linearly from similar to 20x10(10) to 5x10(10) cm(-2) eV(-1) over an energy range extending from 0.05 to 0.25 eV above the bulk Fermi level. (c) 2008 American Institute of Physics.

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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

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This study evaluated the presence of residues after removal of calcium hydroxide [Ca(OH)2] associated with different vehicles. Thirty single-rooted teeth were instrumented to a master apical file #25 using 2.5% NaOCl as main irrigant and 17% trisodium EDTA (ethylenediaminetetraacetic acid) as final agent irrigant. Then, the root canals were dressed with Ca(OH)2 associated with silicone oil (Group 1), 2% chlorhexidine gluconate (Group 2), or propylene glycol (Group 3). After coronal sealing, all teeth were kept in a moist environment at room temperature. After 7 days, the teeth were reopened and medicaments were removed using 5 mL of saline solution and instrumentation with master apical file followed by new irrigation with 5 mL of 2.5% NaOCl. Subsequently, teeth were split longitudinally and assessed by scanning electron microscopy. The wall cleanliness of the cervical and apical thirds of the roots were evaluated and scored by three blinded examiners. Statistical analysis was performed using KruskalWallis and Wilcoxon tests at 5% level of significance. All roots had residues of Ca(OH)2 on the canal walls. All experimental groups had similar results (P > 0.05) regardless of the third evaluated. There was significant difference between the apical and cervical thirds only in Group 3 (P < 0.05). Association of different vehicles to Ca(OH)2 does not influence the persistence of residues on the root canal walls. Microsc. Res. Tech. 2012. (C) 2012 Wiley Periodicals, Inc.